A Bio-Inspired Approach to Selective Inheritance Modeling

Abstract

The conventional inheritance concept adopted in the current Object Oriented Programming (OOP) was applied more than three decades ago. It is acting on is-a hierarchy model, and has some defects; while OOP is trying to be more close to the real life, it is still far from genetics principles. Adopted inheritance concept means that the child class can inherit, and get everything that is public in the parent class automatically. This process has solved many problems, but it does not simulate what is really happening in our life, where each object can gain just the needed properties from the parent class. So, in simple words, conventional inheritance is not selective and is generating identical objects. One of introduced solutions was the selective inheritance. But, while conventional inheritance acts on “is-a” hierarchy model, the works that introduced the selective inheritance were also done on this model and still suffers from some problems. The inspiration from the “real life” genetics has led us to a selective inheritance acting upon a “Composed by” model rather than the “is-a” model, where the properties are classified into several classes according to Composed relation. This paper proposes a Genetic approach to a new model for selective inheritance that is replacing the “is-a” hierarchy model by a “Composed by” one, which reduces the complexity and makes each object has its own definition. After that, it proposes a language extension to be adopted in any object oriented programming language.